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Record W3033726374 · doi:10.1128/msphere.00253-20

Evaluation of a Rapid Point-of-Care Multiplex Immunochromatographic Assay for the Diagnosis of Enteric Fever

2020· article· en· W3033726374 on OpenAlexaff
Shailendra Kumar, Ariana Nodoushani, Farhana Khanam, Alyssa T. DeCruz, Paul Lambotte, Robert McN. Scott, Isaac I. Bogoch, Krista Vaidya, Stephen B. Calderwood, Taufiqur Rahman Bhuiyan, Javan Esfandiari, Edward T. Ryan, Firdausi Qadri, Jason R. Andrews, Richelle C. Charles

Bibliographic record

VenuemSphere · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsUniversity of Toronto
FundersFogarty International CenterNational Institute of Allergy and Infectious DiseasesInternational Centre for Diarrhoeal Disease Research, BangladeshSchool of Medicine, Stanford UniversityRobert Wood Johnson Foundation
KeywordsTyphoid feverEnteric virusEnteric feverMedicinePublic healthPoint-of-care testingVirologyEnvironmental healthVaccinationPoint of careMultiplexImmunologyIntensive care medicineBiologyBioinformaticsPathology

Abstract

fetched live from OpenAlex

Enteric fever remains a significant global problem, and control programs are significantly limited by the lack of an optimal assay for identifying individuals with acute infection. This is especially critical considering the recently released World Health Organization (WHO) position paper endorsing the role of the typhoid conjugate vaccine in communities where enteric fever is endemic. A reliable diagnostic test is needed to assess and evaluate typhoid intervention strategies and determine which high-burden areas may benefit most from a vaccine intervention. Our collaborative team has developed and evaluated a point-of-care serodiagnostic assay based on detection of anti-HlyE and LPS IgA. Our finding of the high diagnostic accuracy of the DPP Typhoid System for the rapid detection of enteric fever has the potential to have significant public health impact by allowing for improved surveillance and for control and prevention programs in areas with limited laboratory capacity.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.074
GPT teacher head0.281
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations22
Published2020
Admission routes1
Has abstractyes

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